Showing papers on "Interface (computing) published in 2017"

Tuning Selectivity of CO2 Hydrogenation Reactions at the Metal/Oxide Interface

Abstract: The chemical transformation of CO2 not only mitigates the anthropogenic CO2 emission into the Earth’s atmosphere but also produces carbon compounds that can be used as precursors for the production of chemicals and fuels. The activation and conversion of CO2 can be achieved on multifunctional catalytic sites available at the metal/oxide interface by taking advantage of the synergy between the metal nanoparticles and oxide support. Herein, we look at the recent progress in mechanistic studies of CO2 hydrogenation to C1 (CO, CH3OH, and CH4) compounds on metal/oxide catalysts. On this basis, we are able to provide a better understanding of the complex reaction network, grasp the capability of manipulating structure and combination of metal and oxide at the interface in tuning selectivity, and identify the key descriptors to control the activity and, in particular, the selectivity of catalysts. Finally, we also discuss challenges and future research opportunities for tuning the selective conversion of CO2 on ...

High performance communication by people with paralysis using an intracortical brain-computer interface

Abstract: People with various forms paralysis not only have difficulties getting around, but also are less able to use many communication technologies including computers. In particular, strokes, neurological injuries, or diseases such as ALS can lead to severe paralysis and make it very difficult to communicate. In rare instances, these disorders can result in a condition called locked-in syndrome, in which the affected person is aware but completely unable to move or speak. Several researchers are looking to help people with severe paralysis to communicate again, via a system called a brain-computer interface. These devices record activity in the brain either from the surface of the scalp or directly using a sensor that is surgically implanted. Computers then interpret this activity via algorithms to generate signals that can control various tools, including robotic limbs, powered wheelchairs or computer cursors. Such tools would be invaluable for many people with paralysis. Pandarinath, Nuyujukian et al. set out to study the performance of an implanted brain-computer interface in three people with varying forms of paralysis and focused specifically on a typing task. Each participant used a brain-computer interface known as “BrainGate” to move a cursor on a computer screen displaying the letters of the alphabet. The participants were asked to “point and click” on letters – similar to using a normal computer mouse – to type specific sentences, and their typing rate in words per minute was measured. With recently developed computer algorithms, the participants typed faster using the brain-computer interface than anyone with paralysis has ever managed before. Indeed, the highest performing participant could, on average, type nearly 8 words per minute. The next steps are to adapt the system so that brain-computer interfaces can control commercial computers, phones and tablets. These devices are widely available, and would allow paralyzed users to take advantage of a range of applications that can be easily downloaded and customized. This development might enable brain-computer interfaces to not only allow people with neurological disorders to communicate, but also assist other people with paralysis in a number of ways.

Miniaturized Battery-Free Wireless Systems for Wearable Pulse Oximetry

Abstract: Development of unconventional technologies for wireless collection, storage and analysis of quantitative, clinically relevant information on physiological status is of growing interest. Soft, biocompatible systems are widely regarded as important because they facilitate mounting on external (e.g. skin) and internal (e.g. heart, brain) surfaces of the body. Ultra-miniaturized, lightweight and battery-free devices have the potential to establish complementary options in bio-integration, where chronic interfaces (i.e. months) are possible on hard surfaces such as the fingernails and the teeth, with negligible risk for irritation or discomfort. Here we report materials and device concepts for flexible platforms that incorporate advanced optoelectronic functionality for applications in wireless capture and transmission of photoplethysmograms, including quantitative information on blood oxygenation, heart rate and heart rate variability. Specifically, reflectance pulse oximetry in conjunction with near-field communication (NFC) capabilities enables operation in thin, miniaturized flexible devices. Studies of the material aspects associated with the body interface, together with investigations of the radio frequency characteristics, the optoelectronic data acquisition approaches and the analysis methods capture all of the relevant engineering considerations. Demonstrations of operation on various locations of the body and quantitative comparisons to clinical gold standards establish the versatility and the measurement accuracy of these systems, respectively.

More features, more tools, more CrysTBox

Abstract: A new release of the CrysTBox software is introduced. The original toolbox allows for an automated analysis of transmission electron microscope (TEM) images and for crystallographic visualization. The existing tools, which are capable of highly precise analyses of high-resolution TEM images, as well as spot, disc and ring diffraction patterns, are extended to include a tool for automatically measuring TEM sample thickness using convergent beam electron diffraction in a two-beam approximation. An implementation of geometric phase analysis is newly available, employing one of the existing tools to identify parameters and indices of crystallographic planes depicted in the input image and allowing easier and more accurate analysis. The crystallographic visualization capabilities are extended as well. Along with the simulated diffraction pattern and atomic structure, a stereographic projection and inverse pole figure tool is newly offered. A new tool able to visualize the atomic structure of two different phases and their interface is also introduced.

Optimizing virtual reality for all users through gaze-contingent and adaptive focus displays.

Abstract: From the desktop to the laptop to the mobile device, personal computing platforms evolve over time. Moving forward, wearable computing is widely expected to be integral to consumer electronics and beyond. The primary interface between a wearable computer and a user is often a near-eye display. However, current generation near-eye displays suffer from multiple limitations: they are unable to provide fully natural visual cues and comfortable viewing experiences for all users. At their core, many of the issues with near-eye displays are caused by limitations in conventional optics. Current displays cannot reproduce the changes in focus that accompany natural vision, and they cannot support users with uncorrected refractive errors. With two prototype near-eye displays, we show how these issues can be overcome using display modes that adapt to the user via computational optics. By using focus-tunable lenses, mechanically actuated displays, and mobile gaze-tracking technology, these displays can be tailored to correct common refractive errors and provide natural focus cues by dynamically updating the system based on where a user looks in a virtual scene. Indeed, the opportunities afforded by recent advances in computational optics open up the possibility of creating a computing platform in which some users may experience better quality vision in the virtual world than in the real one.

Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning

Abstract: We propose a practical state-of-the-art method to develop a machine-learning-based humanoid robot that can work as a production line worker. The proposed approach provides an intuitive way to collect data and exhibits the following characteristics: task performing capability, task reiteration ability, generalizability, and easy applicability. The proposed approach utilizes a real-time user interface with a monitor and provides a first-person perspective using a head-mounted display. Through this interface, teleoperation is used for collecting task operating data, especially for tasks that are difficult to be applied with a conventional method. A two-phase deep learning model is also utilized in the proposed approach. A deep convolutional autoencoder extracts images features and reconstructs images, and a fully connected deep time delay neural network learns the dynamics of a robot task process from the extracted image features and motion angle signals. The “Nextage Open” humanoid robot is used as an experimental platform to evaluate the proposed model. The object folding task utilizing with 35 trained and 5 untrained sensory motor sequences for test. Testing the trained model with online generation demonstrates a 77.8% success rate for the object folding task.

The roles of carrier concentration and interface, bulk, and grain-boundary recombination for 25% efficient CdTe solar cells

Abstract: CdTe devices have reached efficiencies of 22% due to continuing improvements in bulk material properties, including minority carrier lifetime. Device modeling has helped to guide these device improvements by quantifying the impacts of material properties and different device designs on device performance. One of the barriers to truly predictive device modeling is the interdependence of these material properties. For example, interfaces become more critical as bulk properties, particularly, hole density and carrier lifetime, increase. We present device-modeling analyses that describe the effects of recombination at the interfaces and grain boundaries as lifetime and doping of the CdTe layer change. The doping and lifetime should be priorities for maximizing open-circuit voltage (Voc) and efficiency improvements. However, interface and grain boundary recombination become bottlenecks for device performance at increased lifetime and doping levels. This work quantifies and discusses these emerging challenges f...

plotROC: A Tool for Plotting ROC Curves.

Abstract: Plots of the receiver operating characteristic (ROC) curve are ubiquitous in medical research. Designed to simultaneously display the operating characteristics at every possible value of a continuous diagnostic test, ROC curves are used in oncology to evaluate screening, diagnostic, prognostic and predictive biomarkers. I reviewed a sample of ROC curve plots from the major oncology journals in order to assess current trends in usage and design elements. My review suggests that ROC curve plots are often ineffective as statistical charts and that poor design obscures the relevant information the chart is intended to display. I describe my new R package that was created to address the shortcomings of existing tools. The package has functions to create informative ROC curve plots, with sensible defaults and a simple interface, for use in print or as an interactive web-based plot. A web application was developed to reach a broader audience of scientists who do not use R.

Surgical tools configured for interchangeable use with different controller interfaces

Abstract: A surgical tool configured to be interchangeably attached to a first controller interface and a second controller interface that is different from the first controller interface is disclosed.

A Smart Flexible Zinc Battery with Cooling Recovery Ability

Abstract: Flexible batteries are essential for wearable electronic devices. To meet practical applications, they need to be mechanically robust and stable. However, strong or multiple bending may sever the interfacial contact between electrode and electrolyte, causing capacity fading or even battery failure. Herein we present a new cooling-recovery concept for flexible batteries, which involves a temperature-sensitive sol–gel transition behavior of the thermoreversible polymer hydrogel electrolyte. Once a battery has suffered from strong mechanical stresses, a simple cooling process can refresh the electrode–electrolyte interface. The energy-storage capability can be recovered with a healing efficiency higher than 98 %. It is believed that this study not only offers new valuable insights, but also opens up new perspectives to develop functional wearable devices.

Stream-Dataflow Acceleration

Abstract: Demand for low-power data processing hardware continues to rise inexorably. Existing programmable and "general purpose" solutions (eg. SIMD, GPGPUs) are insufficient, as evidenced by the order-of-magnitude improvements and industry adoption of application and domain-specific accelerators in important areas like machine learning, computer vision and big data. The stark tradeoffs between efficiency and generality at these two extremes poses a difficult question: how could domain-specific hardware efficiency be achieved without domain-specific hardware solutions?In this work, we rely on the insight that "acceleratable" algorithms have broad common properties: high computational intensity with long phases, simple control patterns and dependences, and simple streaming memory access and reuse patterns. We define a general architecture (a hardware-software interface) which can more efficiently expresses program with these properties called stream-dataflow. The dataflow component of this architecture enables high concurrency, and the stream component enables communication and coordination at very-low power and area overhead. This paper explores the hardware and software implications, describes its detailed microarchitecture, and evaluates an implementation. Compared to a state-of-the-art domain specific accelerator (DianNao), and fixed-function accelerators for MachSuite, Softbrain can match their performance with only 2x power overhead on average.

Data transmission method and device

Abstract: Embodiments of the present invention provide a data transmission method and device, which are to be applied to a source client, wherein the source client is a client in a foreground running status in a mobile terminal, the mobile terminal, by means of a split-screen function, divides the display screen thereof into a first split screen for displaying a running interface of the source client and a second split screen for displaying a running interface of a target client, the target client is a client in a foreground running status in the mobile terminal. The method comprises: establishing a communication connection between the source client and the target client; receiving a drag instruction for a thumbnail of target data in the source client and moving the thumbnail according to the drag instruction; monitoring whether a data transmission instruction for the target data is received, if yes, transmitting the target data to the target client through the established communication connection. By applying the embodiments of the present invention, users can make full advantage of the split-screen technology, which simplifies data transmission operation.

Comparing Social Robot, Screen and Voice Interfaces for Smart-Home Control

Abstract: With domestic technology on the rise, the quantity and complexity of smart-home devices are becoming an important interaction design challenge. We present a novel design for a home control interface in the form of a social robot, commanded via tangible icons and giving feedback through expressive gestures. We experimentally compare the robot to three common smart-home interfaces: a voice-control loudspeaker; a wall-mounted touch-screen; and a mobile application. Our findings suggest that interfaces that rate higher on flow rate lower on usability, and vice versa. Participants' sense of control is highest using familiar interfaces, and lowest using voice control. Situation awareness is highest using the robot, and also lowest using voice control. These findings raise questions about voice control as a smart-home interface, and suggest that embodied social robots could provide for an engaging interface with high situation awareness, but also that their usability remains a considerable design challenge.

Summarizer: trading communication with computing near storage

Abstract: Modern data center solid state drives (SSDs) integrate multiple general-purpose embedded cores to manage ash translation layer, garbage collection, wear-leveling, and etc., to improve the performance and the reliability of SSDs. As the performance of these cores steadily improves there are opportunities to repurpose these cores to perform application driven computations on stored data, with the aim of reducing the communication between the host processor and the SSD. Reducing host-SSD bandwidth demand cuts down the I/O time which is a bottleneck for many applications operating on large data sets. However, the embedded core performance is still significantly lower than the host processor, as generally wimpy embedded cores are used within SSD for cost effective reasons. So there is a trade-o between the computation overhead associated with near SSD processing and the reduction in communication overhead to the host system. In this work, we design a set of application programming interfaces (APIs) that can be used by the host application to offload a data intensive task to the SSD processor. We describe how these APIs can be implemented by simple modifications to the existing Non-Volatile Memory Express (NVMe) command interface between the host and the SSD processor. We then quantify the computation versus communication tradeoffs for near storage computing using applications from two important domains, namely data analytics and data integration. Using a fully functional SSD evaluation platform we perform design space exploration of our proposed approach by varying the bandwidth and computation capabilities of the SSD processor. We evaluate static and dynamic approaches for dividing the work between the host and SSD processor, and show that our design may improve the performance by up to 20% when compared to processing at the host processor only, and 6when compared to processing at the SSD processor only. CCS CONCEPTS • Computer systems organization → Secondary storage organization; Distributed architectures; Firmware;

SAV2P: Exploring the Impact of an Interface for Shared Automated Vehicles on Pedestrians' Experience

Abstract: To study future communication needs between pedestrians and shared automated vehicles (SAVs), an interface that communicates the intentions of SAVs to pedestrians was designed and implemented in a virtual reality (VR) environment. This enabled the exploration of behaviors and experiences of 34 pedestrians when encountering SAVs, both with and without the interface, in several street crossing situations. All pedestrians assessed the level of perceived safety and comfort directly after each encounter with the SAV. The results show that the pedestrians' level of perceived safety and comfort is higher in encounters with the interface than in encounters without the interface. This may have a positive influence on the acceptance of SAVs, and implies that future SAVs may gain from this, or similar interface.

UNO: uniflying host and smart NIC offload for flexible packet processing

Abstract: Increasingly, smart Network Interface Cards (sNICs) are being used in data centers to offload networking functions (NFs) from host processors thereby making these processors available for tenant applications. Modern sNICs have fully programmable, energy-efficient multi-core processors on which many packet processing functions, including a full-blown programmable switch, can run. However, having multiple switch instances deployed across the host hypervisor and the attached sNICs makes controlling them difficult and data plane operations more complex. This paper proposes a generalized SDN-controlled NF offload architecture called UNO. It can transparently offload dynamically selected host processors' packet processing functions to sNICs by using multiple switches in the host while keeping the data centerwide network control and management planes unmodified. UNO exposes a single virtual control plane to the SDN controller and hides dynamic NF offload behind a unified virtual management plane. This enables UNO to make optimal use of host's and sNIC's combined packet processing capabilities with local optimization based on locally observed traffic patterns and resource consumption, and without central controller involvement. Experimental results based on a real UNO prototype in realistic scenarios show promising results: it can save processing worth up to 8 CPU cores, reduce power usage by up to 2x, and reduce the control plane overhead by more than 50%.

Heterogeneous Information Fusion and Visualization for a Large-Scale Intelligent Video Surveillance System

Abstract: Wide-area monitoring for a smart community can be challenging in systems engineering because of its large scale and heterogeneity at the sensor, algorithm, and visualization levels. A smart interface to visualize high-level information fused from a diversity of low-level surveillance data, and to facilitate rapid response of events, is critical for the design of the system. This paper presents an event-driven visualization mechanism fusing multimodal information for a large-scale intelligent video surveillance system. The mechanism proactively helps security personnel intuitively be aware of events through close cooperation among visualization, data fusion, and sensor tasking. The visualization not only displays 2-D, 3-D, and geographical information within a condensed form of interface but also automatically shows the only important video streams corresponding to spontaneous alerts and events by a decision process called display switching arbitration. The display switching arbitration decides the importance of cameras by score ranking that considers event urgency and semantic object features. This system has been successfully deployed in a campus to demonstrate its usability and efficiency for an installation with two camera clusters that include dozens of cameras, and with a lot of video analytics to detect alerts and events. A further simulation comparing the display switching arbitration with similar camera selection methods shows that our method improves the visualization by selecting better representative camera views and reducing redundant switchover among multiview videos.

An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks.

Abstract: In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments.

Supervisory control and reactive synthesis: a comparative introduction

Abstract: This paper presents an introduction to and a formal connection between synthesis problems for discrete event systems that have been considered, largely separately, in the two research communities of supervisory control in control engineering and reactive synthesis in computer science. By making this connection mathematically precise in a paper that attempts to be as self-contained as possible, we wish to introduce these two research areas to non-expert readers and at the same time to highlight how they can be bridged in the context of classical synthesis problems. After presenting general introductions to supervisory control theory and reactive synthesis, we provide a novel reduction of the basic supervisory control problem, non-blocking case, to a problem of reactive synthesis with plants and with a maximal permissiveness requirement. The reduction is for fully-observed systems that are controlled by a single supervisor/controller. It complements prior work that has explored problems at the interface of supervisory control and reactive synthesis. The formal bridge constructed in this paper should be a source of inspiration for new lines of investigation that will leverage the power of the synthesis techniques that have been developed in these two areas.

Fuzzy Integral With Particle Swarm Optimization for a Motor-Imagery-Based Brain–Computer Interface

Abstract: A brain-computer interface (BCI) system using elec-troencephalography signals provides a convenient means of communication between the human brain and a computer. Motor imagery (MI), in which motor actions are mentally rehearsed without engaging in actual physical execution, has been widely used as a major BCI approach. One robust algorithm that can successfully cope with the individual differences in MI-related rhythmic patterns is to create diverse ensemble classifiers using the subband common spatial pattern (SBCSP) method. To aggregate outputs of ensemble members, this study uses fuzzy integral with particle swarm optimization (PSO), which can regulate subject-specific parameters for the assignment of optimal confidence levels for classifiers. The proposed system combining SBCSP, fuzzy integral, and PSO exhibits robust performance for offline single-trial classification of MI and real-time control of a robotic arm using MI. This paper represents the first attempt to utilize fuzzy fusion technique to attack the individual differences problem of MI applications in real-world noisy environments. The results of this study demonstrate the practical feasibility of implementing the proposed method for real-world applications.

KAML: A Flexible, High-Performance Key-Value SSD

Abstract: Modern solid state drives (SSDs) unnecessarily confine host programs to the conventional block I/O interface, leading to suboptimal performance and resource under-utilization. Recent attempts to replace or extend this interface with a key-value-oriented interface and/or built-in support for transactions offer some improvements, but the details of their implementations make them a poor match for many applications. This paper presents the key-addressable, multi-log SSD (KAML), an SSD with a key-value interface that uses a novel multi-log architecture and stores data as variable-sized records rather than fixed-sized sectors. Exposing a key-value interface allows applications to remove a layer of indirection between application-level keys (e.g., database record IDs or file inode numbers) and data stored in the SSD. KAML also provides native transaction support tuned to support fine-grained locking, achieving improved performance compared to previous designs that require page-level locking. Finally, KAML includes a caching layer analogous to a conventional page cache that leverages host DRAM to improve performance and provides additional transactional features. We have implemented a prototype of KAML on a commercial SSD prototyping platform, and our results show that compared with existing key-value stores, KAML improves the performance of online transaction processing (OLTP) workloads by 1.1X – 4.0X, and NoSQL key-value store applications by 1.1X – 3.0X.